HBaseCon 2013: "Case Studies" Track Preview

HBaseCon 2013 is this Thursday (June 13 in San Francisco), and we can hardly wait!

To complete the “preview” cycle, today we bring you a snapshot of the Case Studies track, which offers a cross-section of the many real-world use cases for Apache HBase. You will learn about how a range of companies across diverse industries use it at the heart of their IT infrastructure to run their business.

  • Multi-tenant Apache HBase at Yahoo!
    Sumeet Singh & Francis Liu, Yahoo!
    The introduction of multi-tenancy has lowered the barriers for all Hadoop users to use HBase. Here you will learn the traditional use cases for HBase at Yahoo!, and new use cases as a result in content management, advertising, log processing, analytics and reporting, recommendation graphs, and dimension data stores. 
  • Near Real Time Indexing for eBay Search
    Swati Agarwal & Raj Tanneru, eBay
    Here the presenters will talk about eBay’s new search indexing platform, and in particular, the HBase-based near real-time indexing capability.
  • Apache HBase at Pinterest: Scaling our Feed Storage 
    Varun Sharma, Pinterest
    In this talk, learn about Pinterest’s experience architecting and scaling its Feed storage on HBase.
  • Deal Personalization Engine with HBase @ Groupon
    Ameya Kantikar, Groupon
    At Groupon, HBase now powers most of the backend technology for real-time delivery of “deal” experience across all platforms, as well as powers batch clusters for consolidated user data.
  • Being Smarter Than the Smart Meter 
    Jay Talreja, Oracle
    DataRaker, now part of the Oracle Utility Software Suite, was architected on HBase to scale to the largest smart meter deployments in the world. This session describes how HBase has provided the raw compute capacity to solve complex data analytics problems previously unavailable using traditional storage platforms.
  • Apache Hadoop and Apache HBase for Real-Time Video Analytics 
    Suman Srinivasan, LongTail Video
    In this talk, the presenters discuss how LongTail Video uses Hadoop for real-time analytics by processing data in frequent batches, its experience with HBase for ingesting millions of aggregate data points and providing real-time results, a brief overview of its HBase schema, and using HBase Thrift and Python in production.
  • ETL for Apache HBase
    Manoj Khanwalkar & Govind Asawa, Experian
    Experian’s ETL framework can source data from various systems, transform it, and persist in HBase. The framework also provides the ability to populate star schema-like structures in HBase by stamping dimensions data to the fact table and the ability to populate multiple aggregate tables in HBase and /or RDBMS in real time or batch mode.
  • Rebuilding for Scale on Apache HBase
    Robert Roland, Simple Measured
    This talk will cover why Simple Measured moved to HBase from MongoDB, how it integrated HBase with the least amount of downtime and impact to its customers, the financial costs of this migration, and where it’s going in the future.
  • Evolving a First-Generation Apache HBase Deployment to Second Generation and Beyond
    Doug Meil, Explorys
    Explorys has been using HBase and Hadoop since HBase 0.20, and here will walk through lessons learned over years of usage from its first HBase implementation through a series of upgrades and changes, including impacts to schema design, data loading, data indexing, data access and analytics, and operational processes.
  • Mixing Low Latency with Analytical Workloads for Customer Experience Management
    Neil Ferguson, Causata
    Causata recently migrated to HBase from its own custom-built data store, and here you will learn the challenges it overcame getting HBase to build customer profiles from many millions of unaggregated data points per second, per server, from many TBs of data.
  • Realtime User Segmentation using Apache HBase: Architectural Case Study
    Murtaza Doctor & Giang Nguyen, RichRelevance
    Behavioral targeting, specifically user segmentation and building personas, is critical for RichRelevance in generating triggers when a user is added to a segment or switches from a segment. In this presentation, you’ll learn not only how the events are captured, but also how they are stored in HBase in real time.
  • Apache HBase, Apache Hadoop, DNA and YOU!
    Jeremy Pollack, Ancestry.com
    Find out how Ancestry DNA used Hadoop and HBase to implement a scalable cleanroom implementation of the GERMLINE algorithm, resulting in a 1700% performance improvement.

If these previews have not convinced you that missing HBaseCon is unthinkable for HBase users/enthusiasts, nothing will! See you on Thursday!

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